Research Horizons

The Visual Suspects

Profile

Alex Godwin, a Ph.D. student in the Information Interfaces Lab, stands in the parking lot behind the Georgia Tech Police Department. One of the lab’s current projects looks at criminal activity by neighborhood.

Alex Godwin is a Ph.D. student in Georgia Tech’s Information Interfaces lab, led by John Stasko, a professor in the School of Interactive Computing. Godwin’s research in visualization and visual analytics focuses on ways to help people understand and investigate information that is important and useful to their lives.

WHERE ARE YOU FROM?
I’m from Taylorsville, North Carolina. It’s a small town in the foothills of the Brushy Mountains. I earned my bachelor’s degree and master’s degree in computer science from the University of North Carolina, Charlotte. I was studying gaming, and a professor was looking for students who were interesting in going beyond the schoolwork to do research. That was my first taste of research, and as I got more into it I shifted towards data visualization.

WHAT MADE YOU DECIDE TO PURSUE A PH.D. FROM GEORGIA TECH?
I worked in industry for five years for a small company that did some game-based research, such as creating hand-held mobile games for soldiers to play that also trained them how to use first aid. One of my favorite parts of my job was when we got a new member of the team and I had the chance to mentor them. I realized academia was one of the few opportunities I would have to mentor on a large scale.

WHY FOCUS ON DATA VISUALIZATION?
I like to think of this as a way to democratize data. This is a way to represent complex data — think of criminal activity or building permits — and present it in a clear way so that people who are affected by it can have a conversation about it in a well-reasoned way without needing an expertise in statistics, crime analysis, or urban planning.

HOW IS YOUR RESEARCH APPLIED?
Recently we used Atlanta’s public federal crime database to create a dashboard that compares crime in different neighborhoods. This could be useful for police officers during their regular beat patrols. They can map out a route based on historical crime analysis. We can optimize crime data so that it looks at a particular time, day, or season. Police officers could sketch a few different routes and see which one takes them by the most violent type of crime at a specific time of day. Or, if there’s been a surge of break-ins, they can focus their patrols along those areas. Police are good at knowing the communities they are policing. This would provide them with a tool to enhance and complement their own knowledge.

WHAT ARE SOME CHALLENGES WITH THIS WORK?
For the crime data it’s important to have police officers in the room, show it to them, and see what is useful. Having an intense evaluation with them over a long period of time takes the work from being just a pretty good idea and turns it into cutting-edge research. It becomes something that is actually meaningful for a lot of people. — Laura Diamond